NODC Standard Product: US Navy Geosat wind/wave data (WWDR) from the Geodetic Mission (NCEI Accession 0054150)

The radar backscatter from a nadir-pointing radar is related to the wind speed and is directly proportional to the normal incidence Fresnel power reflection coefficient and inversely proportional to the mean square slope of the low pass filtered version of the ocean surface [Brown, 1978]. Using an algorithm, radar cross section can be converted to wind speed. There are two wind speed fields on this disc, one computed using the Chelton-Wentz algorithm [Chelton and Wentz, 1986] and one using the Smoothed Brown algorithm [Goldhirsh and Dobson, 1985]. The data on this disc were extracted to form
the larger Geosat dataset in 1988, and at that time these were the two algorithms chosen to compute wind speed. In terms of rms (root mean square) accuracy, the Smoothed Brown is slightly more accurate but has the drawback that it should not be used for wind speeds greater than 14 m/s.

Since 1988 several additional algorithms have been proposed. Appendix B (below) gives three of these algorithms which can easily be used to compute wind speed when using the radar cross section values contained herein. A bibliography is included in Appendix A (below), and the reader is encouraged to read some of the pertinent papers for further clarification of the differences of these algorithms. A general review can be found in Dobson [1993]. The general accuracy of wind speed measurements from Geosat is 1.8 m/s.

Significant wave height (SWH) data on this disc were derived from an algorithm used onboard the spacecraft during the Geosat mission. The SWH is related to the slope of the returned radar pulse. When there are waves present on the ocean, the surface appears rough causing the leading edge of the pulse to intersect the wave crests before the troughs, which results in a broadening of the pulse shape. As the distribution of wave heights broadens, so does the
returned pulse shape. Thus from this knowledge, an algorithm was developed relating the pulse slope to SWH. SWH is defined to be that wave height for which there is a 33 percent probability of waves higher than that value. In addition, if the probability density of wave amplitudes is assumed to be a Rayleigh distribution, then it can be shown that SWH is 4 times the standard deviation of the surface waves [Borgman, 1982]. In the last few years several papers have been published that indicate the onboard SWH algorithm underestimates SWH [Mognard et al., 1991; Carter et al., 1992; Glazman, 1991]. The user may want to consult these publications before using the SWH data. A bibliography has been included which contains these three papers and many others that have used Geosat SWH and wind measurements.

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Appendix A: BIBLIOGRAPHY

Barrick, D. E., Rough surface scattering based on specular point theory IEEE Trans. Ant. and Prop.,AP-16(4) 449-454,1968.

Barrick, D. E., A relationship between the slope probability density function and the physical optics integral in rough surface scattering, Proc. IEEE, 36, 1728-1729, 1968, 1968a.

Barrick, D. E., Wind Dependence of quasi-specular microwave sea scatter, IEEE Trans. Antennas and Propag., AP-22,1135-136, 1974.

Borgman, L.E., Summary of probability laws for wave properties, Proc.Inter. School of Physics (Topics in Ocean Physics), Edited by A.R.Osborne and P.M. Rizzoli, North Holland Pub. Co., 1982.

Brown,G.S., Estimation of Surface wind Speeds Using Satellite-Borne Radar Measurements at Normal Incidence, J. Geosphys. Res., 84(B8), 3974-3978, 1979.

Brown,G.,H.R Stanley, and N. A. Roy, The Wind-speed measurement capability of space-borne radar altimeters, IEE J. Oceanic Eng. OE-6(2) 59-63, 1981.

Cardone, V. J. , J. G. Greenwood, and M. A. Roy, On trends in historical marine wind data, J. Climate, 3, 113-127, 1990.

Carter. D. J. T., P.G. Challenor, and M. A. Srokosz, An assessment of Geosat wave height and wind speed measurements, J. Geophys. Res.,97(C7)11383-11392, 1992.

Chelton, D. B. and P. J. McCabe, A review of satellite altimeter measurement of sea surface wind speed: with a proposed new algorithm, J. Geophys. Res.90,4707-4720, 1985.

Chelton,D. B. and Wentz,F. J., Further Development of an improved altimeter wind speed algorithm, 91(C12), 14150-14260, 1986.

Chelton,D. B., WOCE/NASA altimeter algorithm workshop, U. S. WOCE Tech. Rep. No.2, 1988.

Dobson, E. B.,F. Monaldo, J. Goldhirsh, J. Wilkerson, Validation of Geosataltimeter derived wind speeds and significant wave heights using buoy data, J. Geophys. Res., 92(C10), 1987.

Dobson, E. B., Geosat altimeter wind speed and waveheight measure measurements: The ERM mission, Proceedings of the WOCE/NASA Altimeter Algorithm Workshop, Corvallis, Oregon, U. S. WOCE Tech. Rep. No. 2 1987.

Dobson, E.B., Wind Speed from Altimeters - A Review, JHU/APL S1R-93U-024,1993.

Glazman, R. E. and Pilorz, Effects of sea maturity on satellite altimeter measurements, J. Geophys. Res., 95, (C3), 2857-2870, 1990.

Glazman, R. E., Statistical problems of wind generated gravity
waves arising in microwave remote sensing of surface winds, IEE Trans. Geosci. Remote Sens., 29(1), 135-142, 1991.

Glazman, R. E. and A. Greysukh, Satellite altimeter measurements of surface wind., J. Geophys. Res., 98, (C2), 2475-2483, 1993.

Goldhirsh, J. and E. B. Dobson, A recommended algorithm for the determination of ocean surface wind speed using satellite-borne radar altimeter,Tech. rep. S1R85-005, Appl. Phys. Lab.,Johns Hopkins Univ., Laurel,Md., Mar. 1985.

Jackson, F.C, W. T. Walton, D. E. Hines, B. A. Walter, C. Y. Peng, Sea surface mean square slope from K^u- band backscatter data, J. Geophys. Res. 97(C7), 1992.

Mognard, N. M. and B. Lago, The computation of wind speed and wave height from Geos 3 data, J. Geophys. Res., 84(B8), 1979.

Mognard, N. M., J. A. Johannessen, C. E. Livingstone, D. Lyzenga, R. Shuchman, and C. Russell, Simultaneous observations of ocean surface winds and waves by Geosat radar altimeter and airborne synthetic aperture radar during the 1988 Norwegian continentenatal shelf experiment, J. Geophys. Res. 96,(C6), 1991.

Monaldo, F. Expected differences between buoy and radar altimeter
estimates of wind speed and significant wave height and their implications on buoy-altimeter comparisons, J. Geophys. Res., 93, 2285-2302, 1988.

Tournadre,J, and R. Ezraty, Local climatology of wind and sea state by means of satellite radar altimeter measurements, J. Geophys. Res., 95(C10),18225-18268, 1990.

Townsend, W. F., An initial assessment of the performance achieved by the Seasat-1 radar altimeter, IEE J. of Oceanic Eng. OE-5(2), 1980.

Ulaby, F. T., R.K. Moore, A. D. Fung, Microwave Remote Sensing - Active and Passive, Vol II, Addison-Wesley Publis. Co., 1982.

Wentz, F. J., L. A. Mattox, and S. Peteherych, New algorithms for microwave measurements of ocean winds with application to Seasat and SSM/I, J. Geophys. Res., 91, 2289-2307, 1986.

APPENDIX B: ALGORITHMS TO COMPUTE WIND SPEED FROM RADAR CROSS SECTION

Modified Brown Algorithm
------------------------
6.6 25.5680
6.8 23.7010
7.0 22.0450
7.2 20.5720
7.4 19.2580
7.6 18.0800
7.8 17.0240
8.0 16.0720
8.2 15.2130
8.4 14.4360
8.6 13.7310
8.8 13.0890
9.0 12.4509
9.2 11.7923
9.4 11.1745
9.6 10.5933
9.8 10.0446
10.0 9.52479
10.2 9.03052
10.4 8.55883
10.6 8.10740
10.8 7.67366
11.0 7.25583
11.2 6.85210
11.4 6.46129
11.6 6.08195
11.8 5.71337
12.0 5.35477
12.2 5.00570
12.4 4.66582
12.6 4.33492
12.8 4.01336
13.0 3.70079
13.2 3.39790
13.4 3.10481
13.6 2.82246
13.8 2.55095
14.0 2.29109
14.2 2.10000
14.4 1.90000
14.6 1.59000
14.8 1.40000
15.0 1.15300
15.2 1.09200
15.4 1.03600
15.6 0.98500
15.8 0.93900
16.0 0.89700
16.2 0.85900
16.4 0.82400
16.6 0.79200
16.8 0.76200
17.0 0.73500
17.2 0.71000
17.4 0.68700
17.6 0.66500
17.8 0.64500
18.0 0.62700
18.2 0.61000
18.4 0.59400
18.6 0.57900
18.8 0.56600
19.0 0.55200
19.2 0.54100
19.4 0.53000
19.6 0.51900
19.8 0.50900
20.0 0.50000
20.2 0.49100
20.4 0.48300
20.6 0.47600
20.8 0.46900
21.0 0.46200
21.2 0.45600
21.4 0.45000
21.6 0.44400


Witter-Chelton Algorithm
---------------------------
7.0 20.154
7.2 19.597
7.4 19.038
7.6 18.463
7.8 17.877
8.0 17.277
8.2 16.655
8.4 16.011
8.6 15.348
8.8 14.669
9.0 13.976
9.2 13.273
9.4 12.557
9.6 11.830
9.8 11.092
10.0 10.345
10.2 9.590
10.4 8.827
10.6 8.059
10.8 7.298
11.0 6.577
11.2 5.921
11.4 5.321
11.6 4.763
11.8 4.252
12.0 3.792
12.2 3.378
12.4 3.014
12.6 2.708
12.8 2.447
13.0 2.208
13.2 1.992
13.4 1.818
13.6 1.676
13.8 1.547
14.0 1.419
14.2 1.292
14.4 1.167
14.6 1.056
14.8 0.972
15.0 0.915
15.2 0.873
15.4 0.833
15.6 0.794
15.8 0.755
16.0 0.716
16.2 0.677
16.4 0.637
16.6 0.599
16.8 0.559
17.0 0.520
17.2 0.481
17.4 0.442
17.6 0.403
17.8 0.363
18.0 0.324
18.2 0.285
18.4 0.246
18.6 0.207
18.8 0.167
19.0 0.128
19.2 0.089
19.4 0.050
19.6 0.011


Wu Algorithm
---------------
Radar Cross Section = -4.0 - 10(logbase10[0.009 + 0.012 ln U(sub10)])

Where U(sub10) = U sub 10 = wind speed at 10 meters above the surface
and Radar Cross Section is in decibars.

Note: All algorithms are referenced to 10 meters height above the surface.